Briefings in Bioinformatics

Article	Citations
Dynamic changes of synergy relationship between lncRNA and immune checkpoint in cancer progression	702
cfMethylPre: deep transfer learning enhances cancer detection based on circulating cell-free DNA methylation profiling	456
Melanoma 2.0. Skin cancer as a paradigm for emerging diagnostic technologies, computational modelling and artificial intelligence	395
Analysis of super-enhancer using machine learning and its application to medical biology	376
Hi-C3: a statistical inference-based model for reconstructing higher-order cell–cell communication networks	367
Detection of transcription factors binding to methylated DNA by deep recurrent neural network	323
Clover: tree structure-based efficient DNA clustering for DNA-based data storage	239
Improving drug response prediction via integrating gene relationships with deep learning	234
Computational analyses of bacterial strains from shotgun reads	223
Systematic evaluation of de novo mutation calling tools using whole genome sequencing data	215
PMiSLocMF: predicting miRNA subcellular localizations by incorporating multi-source features of miRNAs	213
Phage quest: a beginner’s guide to explore viral diversity in the prokaryotic world	203
Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis	183
Directed evolution of antimicrobial peptides using multi-objective zeroth-order optimization	173
Computational refinement and multivalent engineering of complementarity-determining region-grafted nanobodies on a humanized scaffold for retaining antiviral efficacy	165
Deep learning reveals determinants of transcriptional infidelity at nucleotide resolution in the allopolyploid line by goldfish and common carp hybrids	153
Computational model for ncRNA research	150
COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2	140
Machine learning–augmented m6A-Seq analysis without a reference genome	138
CharID: a two-step model for universal prediction of interactions between chromatin accessible regions	129
QOT: Quantized Optimal Transport for sample-level distance matrix in single-cell omics	126
Balancing the transcriptome: leveraging sample similarity to improve measures of gene specificity	124
CpGFuse: a holistic approach for accurate identification of methylation states of DNA CpG sites	119
Combining power of different methods to detect associations in large data sets	118
ETLD: an encoder-transformation layer-decoder architecture for protein contact and mutation effects prediction	117

Ensemble classification based feature selection: a case of identification on plant pentatricopeptide repeat proteins	116
Correction to: Addressing barriers in comprehensiveness, accessibility, reusability, interoperability and reproducibility of computational models in systems biology	113
Letter regarding article named ‘Is acupuncture effective in the treatment of COVID-19 related symptoms? Based on bioinformatics/network topology strategy’	111
Addressing scalability and managing sparsity and dropout events in single-cell representation identification with ZIGACL	109
SCSMD: Single Cell Consistent Clustering based on Spectral Matrix Decomposition	109
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network	108
A multichannel graph neural network based on multisimilarity modality hypergraph contrastive learning for predicting unknown types of cancer biomarkers	104
Graph-RPI: predicting RNA–protein interactions via graph autoencoder and self-supervised learning strategies	103
Large-scale predicting protein functions through heterogeneous feature fusion	102
DriverOmicsNet: an integrated graph convolutional network for multi-omics exploration of cancer driver genes	101
Improving the performance of single-cell RNA-seq data mining based on relative expression orderings	100
A novel prognostic framework for HBV-infected hepatocellular carcinoma: insights from ferroptosis and iron metabolism proteomics	99
From intuition to AI: evolution of small molecule representations in drug discovery	98
PLMFit: benchmarking transfer learning with protein language models for protein engineering	96
CLT-seq as a universal homopolymer-sequencing concept reveals poly(A)-tail-tuned ncRNA regulation	95
Blood-based transcriptomic signature panel identification for cancer diagnosis: benchmarking of feature extraction methods	93
A chronotherapeutics-applicable multi-target therapeutics based on AI: Example of therapeutic hypothermia	92
A robust statistical approach for finding informative spatially associated pathways	92
A comprehensive benchmark of tools for efficient genomic interval querying	91
mbDecoda: a debiased approach to compositional data analysis for microbiome surveys	88
Multi-modal domain adaptation for revealing spatial functional landscape from spatially resolved transcriptomics	88
BayesKAT: bayesian optimal kernel-based test for genetic association studies reveals joint genetic effects in complex diseases	88
Clustered tree regression to learn protein energy change with mutated amino acid	86
STEAM: Spatial Transcriptomics Evaluation Algorithm and Metric for clustering performance	83
Ensemble learning based on matrix completion improves microbe-disease association prediction	83
Building multiscale models with PhysiBoSS, an agent-based modeling tool	82
scGAD: a new task and end-to-end framework for generalized cell type annotation and discovery	81
dHICA: a deep transformer-based model enables accurate histone imputation from chromatin accessibility	81
SGNNMD: signed graph neural network for predicting deregulation types of miRNA-disease associations	81
FGeneBERT: function-driven pre-trained gene language model for metagenomics	80
Learning discriminative and structural samples for rare cell types with deep generative model	79
Detecting tipping points of complex diseases by network information entropy	78
DeepCheck: multitask learning aids in assessing microbial genome quality	78
Protein phosphorylation database and prediction tools	77
ULDNA: integrating unsupervised multi-source language models with LSTM-attention network for high-accuracy protein–DNA binding site prediction	76
QTFPred: robust high-performance quantum machine learning modeling that predicts main and cooperative transcription factor bindings with base resolution	76
Protein–DNA binding sites prediction based on pre-trained protein language model and contrastive learning	76
A social theory-enhanced graph representation learning framework for multitask prediction of drug–drug interactions	75
Self-supervised learning with chemistry-aware fragmentation for effective molecular property prediction	75
AptaDiff: de novo design and optimization of aptamers based on diffusion models	74
Making PBPK models more reproducible in practice	74
Novel multi-omics deconfounding variational autoencoders can obtain meaningful disease subtyping	74
Assessing protein model quality based on deep graph coupled networks using protein language model	74
Identification of vital chemical information via visualization of graph neural networks	74
PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information	72
Integrating AlphaFold and deep learning for atomistic interpretation of cryo-EM maps	72
Attribute-guided prototype network for few-shot molecular property prediction	72
IGCNSDA: unraveling disease-associated snoRNAs with an interpretable graph convolutional network	71
Multiple errors correction for position-limited DNA sequences with GC balance and no homopolymer for DNA-based data storage	70
A review on the application of bioinformatics tools in food microbiome studies	70

MicroHDF: predicting host phenotypes with metagenomic data using a deep forest-based framework	69
GAABind: a geometry-aware attention-based network for accurate protein–ligand binding pose and binding affinity prediction	69
Subtype-DCC: decoupled contrastive clustering method for cancer subtype identification based on multi-omics data	67
Machine learning modeling of RNA structures: methods, challenges and future perspectives	67
Distant metastasis identification based on optimized graph representation of gene interaction patterns	66
Clustering scRNA-seq data with the cross-view collaborative information fusion strategy	64
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy	64
HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints	64
scAnno: a deconvolution strategy-based automatic cell type annotation tool for single-cell RNA-sequencing data sets	64
Evaluating large language models for annotating proteins	63
Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing	63
ADENet: a novel network-based inference method for prediction of drug adverse events	63
Deep learning in integrating spatial transcriptomics with other modalities	63
Toward high-efficiency, low-resource, and explainable neuropeptide prediction with MSKDNP	62
A robust and scalable graph neural network for accurate single-cell classification	62
Revealing the antimicrobial potential of traditional Chinese medicine through text mining and molecular computation	61
Deciphering gene contributions and etiologies of somatic mutational signatures of cancer	61
A novel computational model ITHCS for enhanced prognostic risk stratification in ESCC by correcting for intratumor heterogeneity	61
Integrated multimodal hierarchical fusion and meta-learning for enhanced molecular property prediction	61
A review of methods for predicting DNA N6-methyladenine sites	61
Knowledge-guided multi-level network modeling with experimental characterization identifies PRKCA as a novel biomarker and tumor suppressor triggering ferroptosis in prostate cancer	60
Robustness and resilience of computational deconvolution methods for bulk RNA sequencing data	60
HLA3D: an integrated structure-based computational toolkit for immunotherapy	60
TransIntegrator: capture nearly full protein-coding transcript variants via integrating Illumina and PacBio transcriptomes	60
ReCIDE: robust estimation of cell type proportions by integrating single-reference-based deconvolutions	60
Multi-omics regulatory network inference in the presence of missing data	60
SPANN: annotating single-cell resolution spatial transcriptome data with scRNA-seq data	59
Correction to: sciCNV: high-throughput paired profiling of transcriptomes and DNA copy number variations at single-cell resolution	58
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers	58
A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches	57
Inferring kinase–phosphosite regulation from phosphoproteome-enriched cancer multi-omics datasets	57
Phylogenetic inference of inter-population transmission rates for infectious diseases	57
SPNE: sample-perturbed network entropy for revealing critical states of complex biological systems	57
Systematic investigation of the homology sequences around the human fusion gene breakpoints in pan-cancer – bioinformatics study for a potential link to MMEJ	57
TaxaGO: a novel, phylogenetically informed gene ontology enrichment analysis tool	56
Clinical and data-driven optimization of Genomiser for rare disease patients: experience from the Hong Kong Genome Project	56
MiRNA–disease association prediction based on meta-paths	56
scEWE: high-order element-wise weighted ensemble clustering for heterogeneity analysis of single-cell RNA-sequencing data	56
slORFfinder: a tool to detect open reading frames resulting from trans-splicing of spliced leader sequences	55
SGCLDGA: unveiling drug–gene associations through simple graph contrastive learning	55
MAMnet: detecting and genotyping deletions and insertions based on long reads and a deep learning approach	55
Multilevel superposition for deciphering the conformational variability of protein ensembles	55
Paradigms, innovations, and biological applications of RNA velocity: a comprehensive review	54
Robust discovery of gene regulatory networks from single-cell gene expression data by Causal Inference Using Composition of Transactions	54
RiboChat: a chat-style web interface for analysis and annotation of ribosome profiling data	54
TCM-navigator, a deep learning-based workflow for generation and evaluation of traditional Chinese medicine-like compounds for drug development	54
BioWorkflow: Retrieving comprehensive bioinformatics workflows from publications	53
ConSIG: consistent discovery of molecular signature from OMIC data	53
A risk assessment framework for multidrug-resistant Staphylococcus aureus using machine learning and mass spectrometry technology	52
HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses	52
Estimation of non-equilibrium transition rate from gene expression data	52
OmniDoublet: a method for doublet detection in multimodal single-cell sequencing data	52
Deciphering the etiology and role in oncogenic transformation of the CpG island methylator phenotype: a pan-cancer analysis	52
Concepts and methods for transcriptome-wide prediction of chemical messenger RNA modifications with machine learning	51
The improved de Bruijn graph for multitask learning: predicting functions, subcellular localization, and interactions of noncoding RNAs	50
dSCOPE: a software to detect sequences critical for liquid–liquid phase separation	50
Predicting molecular properties based on the interpretable graph neural network with multistep focus mechanism	50
RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins	50
ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA	50
A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma	49
Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information	49
PredLLPS_PSSM: a novel predictor for liquid–liquid protein separation identification based on evolutionary information and a deep neural network	49
BETA: a comprehensive benchmark for computational drug–target prediction	49
LRcell : detecting the source of differential expression at the sub–cell-type level from bulk RNA-seq data	48
scAMAC: self-supervised clustering of scRNA-seq data based on adaptive multi-scale autoencoder	48
Data-driven selection of analysis decisions in single-cell RNA-seq trajectory inference	48
IEPAPI: a method for immune epitope prediction by incorporating antigen presentation and immunogenicity	48
Seq2Topt: a sequence-based deep learning predictor of enzyme optimal temperature	47
Comparative epigenome analysis using Infinium DNA methylation BeadChips	47
Contrastive learning-based computational histopathology predict differential expression of cancer driver genes	47
Denoising adaptive deep clustering with self-attention mechanism on single-cell sequencing data	47
Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders	46
Capturing large genomic contexts for accurately predicting enhancer-promoter interactions	46
BatchDTA: implicit batch alignment enhances deep learning-based drug–target affinity estimation	46
Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis	46
Construct a variable-length fragment library for de novo protein structure prediction	46
SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline	46
A novel approach to study multi-domain motions in JAK1’s activation mechanism based on energy landscape	46
FactVAE: a factorized variational autoencoder for single-cell multi-omics data integration analysis	45
Beyond static structures: protein dynamic conformations modeling in the post-AlphaFold era	45

Inferring single-cell resolution spatial gene expression via fusing spot-based spatial transcriptomics, location, and histology using GCN	45
AI-guided discovery and optimization of antimicrobial peptides through species-aware language model	45
Deep learning in structural bioinformatics: current applications and future perspectives	44
Therapeutic peptides identification via kernel risk sensitive loss-based k-nearest neighbor model and multi-Laplacian regularization	44
Advancing microbial diagnostics: a universal phylogeny guided computational algorithm to find unique sequences for precise microorganism detection	43
Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis	43
D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer	43
A novel heterophilic graph diffusion convolutional network for identifying cancer driver genes	43
scDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning	43
CHAI: consensus clustering through similarity matrix integration for cell-type identification	43
Optimized phenotyping of complex morphological traits: enhancing discovery of common and rare genetic variants	43
Efficient prediction of peptide self-assembly through sequential and graphical encoding	43
PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization	43
A comprehensive benchmarking of differential splicing tools for RNA-seq analysis at the event level	43
Drug repositioning based on weighted local information augmented graph neural network	43
MulNet: a scalable framework for reconstructing intra- and intercellular signaling networks from bulk and single-cell RNA-seq data	42
EDS-Kcr: deep supervision based on large language model for identifying protein lysine crotonylation sites across multiple species	42
AMDBNorm: an approach based on distribution adjustment to eliminate batch effects of gene expression data	42
Correction to: Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model	42
Correction to: PHR-search: a search framework for protein remote homology detection based on the predicted protein hierarchical relationships	42
iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution	42
Learning genotype–phenotype associations from gaps in multi-species sequence alignments	42
Incremental modelling and analysis of biological systems with fuzzy hybrid Petri nets	42
GiGs: graph-based integrated Gaussian kernel similarity for virus–drug association prediction	41
Predictive modelling of acute Promyelocytic leukaemia resistance to retinoic acid therapy	41
MetaGeno: a chromosome-wise multi-task genomic framework for ischaemic stroke risk prediction	41
A kinetic model for solving a combination optimization problem in ab-initio Cryo-EM 3D reconstruction	41
PepTCR-Net: prediction of multi-class antigen peptides by T-cell receptor sequences with deep learning	41
Single-cell mosaic integration and cell state transfer with auto-scaling self-attention mechanism	41
Mapping cancer heterogeneity: a consensus network approach to subtypes and pathways	41
Evaluation of single-cell RNAseq labelling algorithms using cancer datasets	40
CRISP: a deep learning architecture for GC × GC–TOFMS contour ROI identification, simulation and analysis in imaging metabolomics	40
Matrix reconstruction with reliable neighbors for predicting potential MiRNA–disease associations	40
MegSite: an accurate nucleic acid-binding residue prediction method based on multimodal protein language model	40
Predicting miRNA-disease associations based on graph attention networks and dual Laplacian regularized least squares	40
DRdriver: identifying drug resistance driver genes using individual-specific gene regulatory network	40
Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network	39
A tool for feature extraction from biological sequences	39
ComABAN: refining molecular representation with the graph attention mechanism to accelerate drug discovery	39
An efficient curriculum learning-based strategy for molecular graph learning	39
Current approaches and outstanding challenges of functional annotation of metabolites: a comprehensive review	39
TP53_PROF: a machine learning model to predict impact of missense mutations in TP53	39
An automatic immunofluorescence pattern classification framework for HEp-2 image based on supervised learning	39
HHOMR: a hybrid high-order moment residual model for miRNA-disease association prediction	39
The landscape of the methodology in drug repurposing using human genomic data: a systematic review	39
Interpretable artificial intelligence model for accurate identification of medical conditions using immune repertoire	39
MGEGFP: a multi-view graph embedding method for gene function prediction based on adaptive estimation with GCN	39
Identify potential drug candidates within a high-quality compound search space	39
Improved prediction of DNA and RNA binding proteins with deep learning models	38
Prediction of multi-relational drug–gene interaction via Dynamic hyperGraph Contrastive Learning	38
Bioinformatics toolbox for exploring target mutation-induced drug resistance	38
Machine learning-assisted substrate binding pocket engineering based on structural information	38
Differentially expressed genes prediction by multiple self-attention on epigenetics data	38
Current computational tools for protein lysine acylation site prediction	37
scIAE: an integrative autoencoder-based ensemble classification framework for single-cell RNA-seq data	37
Spatially contrastive variational autoencoder for deciphering tissue heterogeneity from spatially resolved transcriptomics	37
SAM-TB: a whole genome sequencing data analysis website for detection of Mycobacterium tuberculosis drug resistance and transmission	37
SAM-DTA: a sequence-agnostic model for drug–target binding affinity prediction	37
Whole-genome bisulfite sequencing data analysis learning module on Google Cloud Platform	37
BloodNet: An attention-based deep network for accurate, efficient, and costless bloodstain time since deposition inference	37
Multi-level multi-view network based on structural contrastive learning for scRNA-seq data clustering	37
Advancing edge-based clustering and graph embedding for biological network analysis: a case study in RASopathies	37
HINGRL: predicting drug–disease associations with graph representation learning on heterogeneous information networks	36
GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering	36
Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models	36
A deep learning method for predicting metabolite–disease associations via graph neural network	36
scEGG: an exogenous gene-guided clustering method for single-cell transcriptomic data	35
Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion	35
CACIMAR: cross-species analysis of cell identities, markers, regulations, and interactions using single-cell RNA sequencing data	35
Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics	35
toxCSM: comprehensive prediction of small molecule toxicity profiles	35
Learning single-cell chromatin accessibility profiles using meta-analytic marker genes	35
CosGeneGate selects multi-functional and credible biomarkers for single-cell analysis	35
A parameter-free deep embedded clustering method for single-cell RNA-seq data	35
siRNADiscovery: a graph neural network for siRNA efficacy prediction via deep RNA sequence analysis	35
Transfer learning of clinical outcomes from preclinical molecular data, principles and perspectives	35
Predicting differentially methylated cytosines in TET and DNMT3 knockout mutants via a large language model	35
Circling in on plasmids: benchmarking plasmid detection and reconstruction tools for short-read data from diverse species	34
Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis	34
Combining evolution and protein language models for an interpretable cancer driver mutation prediction with D2Deep	34
NSCGRN: a network structure control method for gene regulatory network inference	34
A review of biomedical datasets relating to drug discovery: a knowledge graph perspective	34
Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network	34
Disrupting explicit encoding paradigms: property-interactive transformers decode T-cell receptor specificity beyond dataset biases	34
Data-driven patient stratification of UK Biobank cohort suggests five endotypes of multimorbidity	34
MUSCLE: multi-view and multi-scale attentional feature fusion for microRNA–disease associations prediction	34
Multimodal deep learning for biomedical data fusion: a review	33
Benchmarking large language models for genomic knowledge with GeneTuring	33
Exploring the kinase-inhibitor fragment interaction space facilitates the discovery of kinase inhibitor overcoming resistance by mutations	33
Benchmarking genome assembly methods on metagenomic sequencing data	33
Correction to: Adjustment of scRNA-seq data to improve cell-type decomposition of spatial transcriptomics	33
Research progress of miRNA–disease association prediction and comparison of related algorithms	33
EGRET: edge aggregated graph attention networks and transfer learning improve protein–protein interaction site prediction	33
A comprehensive benchmark study of methods for identifying significantly perturbed subnetworks in cancer	33
GAEDGRN: reconstruction of gene regulatory networks based on gravity-inspired graph autoencoders	33